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Machine Learning Engineer Opt Jobs in New Jersey

Purple Drive

Machine Learning Engineer

Newark, NJ

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$114K - $157K/yr

SageSure is a leader in catastrophe-exposed property insurance, seeking a Senior Machine Learning Engineer to optimize orchestration processes and ensure efficient model deployment. The role involves ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

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Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
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Machine Learning Engineer Opt jobs near you

Machine Learning Engineer

Purple Drive

Newark, NJ

Other

Retirement

Posted 23 days ago

Job description

Overview:
Role: Machine Learning Engineer
As a Machine Learning Engineer, you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create measurable business value. You will collaborate closely with business stakeholders, data scientists, and cross-functional engineering teams to transform ideas into scalable, production-ready systems. This role requires both strong technical expertise and leadership ability to guide a small team and deliver impactful solutions.
Key Responsibilities
  • Lead and deliver machine learning projects from inception through production, building strong relationships with business partners and cross-functional teams.
  • Collaborate with business leaders and subject matter experts to define success criteria and optimize products, features, and models.
  • Partner with data scientists to design, implement, and train machine learning models.
  • Work with infrastructure teams to enhance architecture, scalability, stability, and performance of ML platforms.
  • Design and optimize data pipelines to support high-performance ML model training and inference.
  • Extend and customize machine learning libraries and frameworks for project-specific needs.
  • Define and implement model monitoring, governance, and operationalization processes for ML solutions.
  • Establish objectives and own the technical roadmap for ML platforms, ensuring delivery of results.
  • Define and promote standards of engineering and operational excellence for ML systems.
  • Apply architectural best practices in the delivery of data science and AI solutions.
Required Skills & Experience
  • Strong background in software engineering with proven experience as a Machine Learning Engineer.
  • Bachelor's degree in Computer Science, Computer Engineering, or related field; Master's preferred.
  • Advanced proficiency in Python, Java, and Scala with solid CS fundamentals (algorithms, data structures, multithreading).
  • Hands-on experience with Generative AI, LangChain, and RAG-based techniques.
  • Expertise in ML/DL libraries such as XGBoost, Scikit-learn, TensorFlow, and PyTorch.
  • Experience building and deploying ML solutions on public clouds (AWS, GCP).
  • Familiarity with ML platforms such as SageMaker, H2O, and DataRobot.
  • Strong knowledge of the ML lifecycle, including containerization, batch vs. real-time inference, and application security.
  • Proven track record in developing and deploying production-grade ML applications with cloud-based automation pipelines.
  • Experience working in Agile/Scrum environments with multiple stakeholders.
  • Excellent communication, collaboration, and problem-solving skills with thought leadership and innovative thinking.
Nice-to-Have
  • Experience with search platforms (e.g., Solr, Elasticsearch).
  • Hands-on experience building recommender systems.
  • Exposure to graph databases (e.g., Neo4j).
  • Familiarity with CI/CD tools (e.g., Jenkins).
  • Domain knowledge in Financial Services, Insurance, or 401K.
  • AWS Solutions Architect certification.

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